code: def test_lfda(self):
      lfda = LFDA(k=2, n_components=2)
      lfda.fit(self.X, self.y)
      res_1 = lfda.transform(self.X)
  
      lfda = LFDA(k=2, n_components=2)
      res_2 = lfda.fit_transform(self.X, self.y)
  
      # signs may be flipped, that's okay
      assert_array_almost_equal(abs(res_1), abs(res_2))
  
file_path: metric-learn/test/test_fit_transform.py
imports: import unittest
  import numpy
  from sklearn.datasets import load_iris
  from numpy.testing import assert_array_almost_equal
  from metric_learn import LMNN, NCA, LFDA, Covariance, MLKR, LSML_Supervised, ITML_Supervised, SDML_Supervised, RCA_Supervised, MMC_Supervised
label_desc: Use image node_id 8 for calling the TestFitTransform obj's underlying member method code with example usage: obj.test_lfda() without return types